Benefits and Challenges of Big Data in Food Industry and Healthcare Sector

This report discusses the benefits and challenges of using big data in the food industry and healthcare sector. It explores how big data can improve operational efficiency, customer satisfaction, and patient care. The report also highlights the challenges associated with implementing big data in these industries.

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Table of Contents
Introduction...........................................................................................................................................1
One of the chosen industry- Food industry........................................................................................1
Benefits of using Big Data in case of McDonalds.............................................................................2
Associated challenges of big data in case of McDonalds...................................................................3
Second industry selected- Healthcare sector......................................................................................4
Significance of Big Data in health care sector...................................................................................4
Associated challenges of big data in case healthcare sector...............................................................6
Value gained by big data.......................................................................................................................7
Current techniques and technologies...................................................................................................10
Conclusion...........................................................................................................................................14
References...........................................................................................................................................15

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Introduction
Big data is a technique that is used to main the structured, semi structured and unstructured
data. This technology has gained importance in the past years as this is used to control large
amount of data. It works on 3Vs like volume, variety and velocity. This report helps in
understanding the concept of big data and the significance of big data. The way in which big
data has impacted McDonalds has also been discussed. The industry chosen for this report is
McDonalds (John Walker, 2014). The need of big data arrived because organisations are not
able to handle large amount of data. They manage the existing as well as new data over the
cloud. In this report the high level architecture that is used by big data is discussed along with
its working principal (Gandomi & Haider, 2015) . Big data increases the efficiency to
perform operations over network. The data is collected from different sources like mobile
phones, emails, applications and data bases (Wu, Zhu, Wu & Ding, 2014).
One of the chosen industry- Food industry
The industry that has been selected in this report is food industry to be more précised
McDonalds is selected. It is an American company that started in 1940 by Richard and
Maurice. This company offer various kinds of fast food and beverages to the customers like
burger, col drinks, coffee and many more. This organisation was converted into a franchise
industry this lead to development of many branches of McDonalds. The headquarters of
McDonalds is shifted to Chicago in 2018 from Oak (Stephens, et.al, 2015). It is a popularly
known food industry that is serves various products like French fries, deserts, chicken
product and much more. In this report the proposals and ways in which big data technology
can be adopted are discussed (Wang, Gunasekaran, Ngai & Papadopoulos, 2016). In case of
McDonalds they have a wide variety of data that need to be managed as they communicate
with many users daily(Chen, Mao & Liu, 2014) . Thus, big data is used to store and manage

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the data efficiently by using advanced processes that avoids the risk. In the present date, here
are approximately 37,250 restaurants located all over the world. If considering the operating
income of the company in 2017 it was found as $9.55 (Kwon, Lee & Shin, 2014). The
company has many users thus the main problem faced by the organisation is managing large
amount of data set(Wamba, Akter, Edwards, Chopin & Gnanzou, 2015) . It was found that
McDonalds have adopted the use of big data technique to manage the structured as well as
unstructured data.
Benefits of using Big Data in case of McDonalds
Big data technology has helped the company to fulfil its business priority like increasing the
clients, expanding the business world wide, serving the services at best customer satisfaction.
Big data has proved to be beneficial for the company as it collects the information on the
basis of interest of customers (Xiang, Schwartz, Gerdes & Uysal, 2015). In past years, the
company has faced various challenges in terms of quality, delivery and lack of clients. By
making use of big data the company have found the areas in which they should grow (Kwon,
Lee & Shin, 2014). The services are offered according to the interest of clients. The company
has invested in 2017 on many technologies and techniques like wireless communication,
internet of things and many more. Sill there was no change in the overall process. Lately, by
implementing big data services business improved customer satisfaction. Big data has been
widely used in all the industry and it has revolutionized food and beverages industry too. It
helps in optimizing the customer service(Assunção, Calheiros, Bianchi, Netto & Buyya,
2015) . The major benefits of big data in food and beverage industry is that it offers
optimized and timely delivery by using various data analysis tools (Xiang, Schwartz, Gerdes
& Uysal, 2015). Big data collects the information from various sources like internet traffic,
communication channels, routers and many more. Big data is beneficial as it predicates the
time that might be taken to deliver the product to the customers. This helps in updating the

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client regarding all the information. It analyses the market trend and then delivers the services
with best quality (Bates, Saria, Ohno-Machado, Shah & Escobar, 2014). Thus it can be said
that big data can improve the operational efficiency (Archenaa & Anita, 2015). The other
benefit that is gained by big data in food industry is sentimental analysis. It monitors the
behaviour of customers, the negative emotion is analysed and then improvement is made. Big
data analysis the change in the demand and then impact the operations. The other goal of big
data in food industry is to offer customer centric experience (Bates, Saria, Ohno-Machado,
Shah & Escobar, 2014). Big data analysis has made tracking, collection and making decision
easier. For example, McDonalds uses the data from mobile phones application by tracking
the food habits a liking of a person. This is become possible only by big data. In food
industry big data has helped in analysing the input by considering all the parameters (Wang,
Kung & Byrd, 2018).
McDonalds have started a data-driven approach to understand the circumstances. It identifies
the ways and area in which improvement could be done. It has optimized the fast food chain
by optimize customers experience. Big data analytics helps in putting the input from all the
sources in one place (Belle, Thiagarajan, Soroushmehr, Navidi, Beard & Najarian, 2015).
Associated challenges of big data in case of McDonalds
Some of the challenges that associated with big data in case of McDonalds are discussed. One
major concern is lack of security that increases the chances of data breaches (Assunção,
Calheiros, Bianchi, Netto & Buyya, 2015). Apart from that, the employees and staff are not
aware about the use of big data and they are not talented enough to work on such tools. It is a
complex task to match the increasing demand of McDonalds by big data (Luo, Wu,
Gopukumar & Zhao, 2016).

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Thus, the major drawbacks that are observed in food industry are dealing with the data
growth. Additionally, it is also difficult to generate the insights in timely manner. It is
challenging to recruit the big data expert from the market (Belle, Thiagarajan, Soroushmehr,
Navidi, Beard & Najarian, 2015).
Second industry selected- Healthcare sector
The other industry that is selected in this report is health scope corporate, from health care
domain. It is an Australian company that operates many medical centres and private hospitals
and offer international services. The headquarter of the company is in Melbourne it operates
many clinics and hospitals.
Significance of Big Data in health care sector
Big data is very useful in healthcare domain as it supports patients to experience efficient
operations. Top benefits of using big data in health care industry are advanced patient care. It
helps in maintaining electronic health care records from any geographical location. It allows
doctors to provide quality care and offer advanced medical care. The use of big data by
health care companies is very significant as they examine the historical records and analyses
staff efficiency (Hashem, Yaqoob, Anuar, Mokhtar, Gani & Khan, 2015). It supports the
companies by cutting down the overall cost and it also reduces the errors as operations are
made automatic. Big data technique helps in having a deeper analysis about the genomes so
that correct treatment can be offered (Xiang, Schwartz, Gerdes & Uysal, 2015).
The application of big data in healthcare has various life saving benefits. The treatment
plans are modelled and modified according to the analyses of information. Doctors are able to
track the past performance of patient and then prevention strategies are developed. They
make use of data driven approach to track the inventory and empower the ways in which
patients’ health could be enhanced (Singh, Guntuku, Thakur & Hota, 2014).

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(Source: https://www.businesswire.com/news/home/20180207005640/en/Top-Benefits-Big-
Data-Healthcare-Industry-Quantzig)
Healthcare industry needs big data for offering advanced patient care, finding better treatment
for disease and to improve the operational efficiency. Apart from that, cost factor is
increasing day by day in the healthcare sector. Thus, big data is a cost effective approach and
also serve as channel to share patient’s information from one place to other. It helps in
predicating the staffing of patient. It has helped the hospitals and many clinics to reduce the
unnecessary labour cost (Belle, Thiagarajan, Soroushmehr, Navidi, Beard & Najarian, 2015).
Big data in medicines helps in maintaining the electronic records that allow patients to share
their information using secure channels. Apart from that doctors can monitor the operations
and records from any location. Other way big data have helped in healthcare sector is offering
real time alerting. The decisions are taken by predicating the situation. It also prevents opioid
abuse by tackling the problem (LaValle, Lesser, Shockley, Hopkins & Kruschwitz, 2011).
The goal of big data in healthcare is to help doctors to make data driven decisions and
improve the treatment plan.

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Thus, it can be concluded from all the research that big data predicts the daily patients
staffing and also allow doctors to use electronic health records. They also proved real time
alerting for instant care. It enhances the patient engagement by using health data fir better
informed strategic planning (Chen, Chiang & Storey,2012). It is beneficial as it reduces fraud
information and enhances data security. In short it can be said that it has expanded the
diagnostic services by allow patients as well as experts to access the medical condition. It has
also reduced the cost by working on prediction data that reduces the chances of errors and
improves performances.
Associated challenges of big data in case healthcare sector
Healthcare industry also faces various challenges some of them are discussed below. One of
the challenges that are observed is data aggregation, as the data related to medical conditions
is widely spread across many hospitals, personal reports, government authorities, etc. Thus, it
is difficult to collect and arrange the data from different sources. Thus collecting the data at
requires various steps like data cleaning and many more (Riggins & Wamba, 2015). The
other issue in healthcare sector is storage thus it is problematic to ensure that system can
access the data at any time. It is expected to keep the healthcare data safe and up-to-date
(Kwon,Lee & Shin, 2014).
Big data is massive and follows heterogeneous structure, thus it becomes difficult to classify
the data in healthcare. The potential challenge of big data analytics is accessing the
information (Riggins & Wamba, 2015). Therefore, it is critical to outline some of challenges
for big data applications in healthcare. The other challenge is that there are issues related to
data quality, inconsistency, instability and validation issues. Other issue that is seen is related
to utility and integration in clinical practices. It is important to solve these challenges so that
the application of big data technology in medical sector can be fastened (Kwon,Lee & Shin,
2014). Additionally patient’s outcome can be improved by reducing waste of resources in

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healthcare. In health care industry one the challenges associated with big data is validating
the data. Irrelevant information can be dangerous while taking decisions (Bates, Saria,
Ohno-Machado, Shah & Escobar, 2014).
Value gained by big data
Big data have added value to each industry from building new capabilities and facilitate
decision-making. It has offered better marketing in every sector by provider customer valued
services and offering opportunities and increasing the operational efficiency (Fan, Lau &
Zhao, 2015). Big data approach has been used by every industry to manage the data
effectively.
(Source: http://vikramaditya.vmokshagroup.com/vmokshagroup-dev/machine-learning-big-
data-analytics/)
Big data make use of technology like database, distributed storage, predictive analytics, data
visualisation and various knowledge discovery tools. Big data have applications in every
industry it is widely influenced the education world (LaValle, Lesser, Shockley, Hopkins &
Kruschwitz, 2011). It offers digital courses and allow learner to gain education from any

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corner. Big data also adds value in the health care sector. Like it reduces the cost of treatment
by removing the chances of having unnecessary diagnosis. It also helps in predicating the
outbreaks of epidemics by taking preventive measures. It also avoids preventable disease by
simple tracking the conditions at early stage (LaValle, Lesser, Shockley, Hopkins &
Kruschwitz, 2011). Apart from that patients can take evidence based medicines that have
been suggested after analysing the past records (Chen, Chiang & Storey,2012).
Big data have also added value in public sector like it is used by government authorities to
remain updated among various fields like agriculture and other sectors. It is also used in
communication, media and other entertainment sectors (Bates, Saria, Ohno-Machado, Shah
& Escobar, 2014). These are used for analysing the weather pattern by collecting the
information from satellites and then decisions are taken accordingly. Rise of big data has also
used in transportation industry as it is used for route planning, congestion management and
traffic planning (Chen, Chiang & Storey,2012). It is also used to detect all the illegal
activities.
Big data is also use in security exchange programs to monitor the financial market thus all the
criminal activities can be tracked easily (Assunção, Calheiros, Bianchi, Netto & Buyya,
2015). Additionally, many hospitals work on the data collected from a cell phone app that
allow doctors to use confirmation based medicine (Jagadish, Gehrke,
Labrinidis,Papakonstantinou, Patel, Ramakrishnan & Shahabi, 2014). It is a best way for
analysing the healthcare related information and taking faster decisions so that steps could eb
taken to improve the effect of chronic disease.

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(Source: https://itw01.com/V58ZVEX.html)
Thus, it be stated that big data is widely used in every sector. It is used in banking sector for
monitoring all the financial related markets to reduce fraud transaction. Big data tools helps
in predicating all the illegal happenings over the network (Assunção, Calheiros, Bianchi,
Netto & Buyya, 2015). Big data applications also help in keeping an eye on all the latest and
trending activities so that decisions are taken accordingly. It is also used in sports sector to
understand the pattern and analyse of performance of players. Various sports events that
occur every year like world cup, FIFA etc. make use of big data analytics (Varian, 2014).
It has also offered value in education by monitoring the performance of students and mapping
out the interest. Thus big data have proved to be beneficial in finding out the area of interest
by analysing the past records. It has offered benefits by empowering management to make
better decisions (Jagadish, Gehrke, Labrinidis,Papakonstantinou, Patel, Ramakrishnan &
Shahabi, 2014). It also helps in identifying the trend to stay competitive. It also increases the
efficiency and commitment in handling core task. It also identifies the opportunities in the
market.
Current techniques and technologies
Some of the techniques and technologies that could be used to capture value from big data are
discussed. There are technologies that enable big data analytics:
 Predictive analytics
 Data virtualization
 Data integration
 Stream analytics
 In memory data fabric

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 Data processing
 Data quality
 NoSQL data bases
 Knowledge discovery tools
 Distributed storage
(Source: https://www.business2community.com/big-data/10-key-technologies-enable-big-
data-analytics-businesses-01959062)
Predictive analytics- It is technique that is used to implement big data and it also eliminates
the risk of making irreverent decisions (Wamba, Akter, Edwards, Chopin & Gnanzou,

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2015). The solution of predictive analytics is to analyse the information by processing it and
then evaluating the data for optimized result.
Databases- These are used to store the data that could be used to manage the data effectively.
Stream analytics-It allows uses to access the data from any location and by using various
steps like filtering, aggregation and various kinds of data (Wamba, Akter, Edwards, Chopin
& Gnanzou, 2015).
Data virtualization- It is a technique through which data can be retrieved without practically
restriction. Like the data formats that could be used and the location where data is stored, it is
one of the best technique that is used in big data technologies (Kitchin, 2014).
Knowledge discovery tool- These tools are used to analyse the data from different sources
that can be either structured or unstructured.
The fundamental benefits associated with big data are that it transforms economies by
delivering a new wave of productive growth. This brings many attractive opportunities in
every field. On the other hand, there are various challenges associated with big data (Kitchin,
2014). Like Collecting and storing big data does not create any business value. Value is
formed only after the data is analysed and acted on. Big data needs extraordinary techniques
to efficiently process large volume of data within limited run times (Singh, Guntuku, Thakur
& Hota, 2014). Big data analytics is a way of collecting, organizing and analysing the
information so that new patterns could be discovered.
Some other techniques of big data is business intelligence analytical processing that make use
of interactive analyse of multidimensional data. Cluster analysis is one such technique in
which objects are segmented into different groups of same properties. Other big data
technique is textual analysis in which computer programs are analysed using some natural

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language (Gandomi & Haider, 2015). Big data is also used in marketing and advertisement by
visualizing the interest of clients.
One common technology of big data is Hadoop that is not easy to control and manage. This is
designed to improve the performance and reduce the complexity that is faced in big data. It
has the capacity of analysing and processing the large data sets. Hadoop has an ability to run
programs and have fault tolerance (Chen, Mao & Liu, 2014).
Some of the profits of Big Data analytics comprises of identifying the root causes of
disappointments and problems in real time (Chen, Mao & Liu, 2014). It also understands the
potential of data-driven marketing. Apart from that it helps in generating customer interests
and then offering the services based on their buying habits. It also improves client
engagement by improving customer devotion.

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Conclusion
It can be concluded from this report that big data have a wide significant in every sector. This
report is completely based on how big data has impacted on various industries. The two
industries that have been focused in this report is food and health care sector. The food
industry that has been selected is McDonald; it is an American company that deliver fast food
services to their customer by analysing the data. It is used to control and manage both
structured and unstructured data. The challenges that are faced due to big data are also
discussed. Big data has added value in each industry by the Big Data initiative from building
new capabilities and facilitate decision-makers. Big data analytics and current techniques and
technologies used to capture the data are discussed. Thus it can be stated that big data refers a
large data set that is used to analyse huge data sets. It is a trending technology that is used to
handle both the structured as well as unstructured data.

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